Why you should care

A recent study stokes Ebola fears because it can’t forecast how big the current epidemic could get. 

Panic has swept the public faster than Ebola itself in recent weeks, as Thomas Eric Duncan became the first person to die of the disease in the U.S., and the nurse treating him at Texas Presbyterian Hospital also fell ill. A second health worker at the hospital tested positive, as well as a Spanish nurse’s assistant who contracted Ebola after treating a patient, but who was recently cleared of the disease.

But here’s the most jarring news: A new study suggests we may have no way of predicting how far the epidemic will go.

According to a little noticed study, published last month in the journal eLife, the typical mathematical model that describes the eventual scale of past outbreaks simply doesn’t apply to what global health experts consider the worst Ebola epidemic on record. “We’re in uncharted waters,” Thomas House, a research fellow at the University of Warwick Mathematics Institute and the study author, told OZY. “The scale of this outbreak is much larger than any seen before, so it’s very hard to predict.”

The current Ebola outbreak to date is spreading much faster than the model predicts.

To be sure, the scale of the disease has not reached anything close to some others of recent decades. So far, Ebola has sickened 8,914 people and killed 4,447. By comparison, the total number of AIDS cases reported to the World Health Organization hit 20,303 at the end of 1985, about a year after scientists discovered HIV, while 414,000 people were confirmed to have contracted H1N1 in October 2009, a little more than six months after the virus surfaced in Mexico.

And not surprising, health officials are trying to assure the world that even if we can’t anticipate the epidemic’s spread, that doesn’t mean we can’t turn the tide. Agencies from the CDC to the WHO believe that it’s still possible to stop the disease’s spread by isolating patients and with safer burial practices that minimize contact with the body.

But that hasn’t stopped top agencies from trying to put some figures on all this. Just last week, the World Health Organization predicted that by December, Ebola could strike 10,000 people per week in West Africa if the world doesn’t beef up response efforts. The WHO also ratcheted its mortality rate estimate up to 70 percent, much higher than the 50 percent reported dead.

Princess Manjoe crying after the dead of a man caused by Ebola, in Monrovia, Liberia, on October 14, 2014.

Princess Manjoe cries after a man dies from Ebola in Monrovia, Liberia.

The WHO’s numbers were estimates; it’s “probably true” that the severity of the current outbreak can’t be predicted, said agency spokesperson Daniel Epstein. Hard-to-predict social factors have a bigger hand in the current outbreak. Unlike in Central Africa, where earlier outbreaks occurred, burial practices in West Africa often include bathing, dressing and kissing the body of the diseased — a surefire way to pass on the deadly disease. The current outbreak also emerged in an urban, high-traffic area that had already been ravaged by an outbreak of Lassa fever, whose symptoms can easily be mistaken for those of Ebola.

In the University of Warwick study, House analyzed the number of cases, deaths and other data from the 24 Ebola outbreaks the WHO reported since the virus first reared its head in Sudan in 1976. Based on these data, he designed a mathematical model to track each outbreak’s scale.

Infectious disease models often hinge on chance events, such as people’s location when they’re most likely to spread the disease, the travel patterns of others with whom they come into contact, or their proximity to medical facilities. House modeled past Ebola outbreaks based on two key chance events: the initial number of cases and level of infectiousness — the amount of viral particles sufficient to cause disease — once the epidemic kicked into gear.

Worst-case scenario: Cases double until only those who have recovered from or are less susceptible to the disease remain.

Plugging the chance event data for each outbreak into House’s model yielded its eventual scale — but not the scale of the current outbreak to date, which is spreading much faster than the model predicts. Consistent with the WHO’s recent announcement, “the most likely thing to see is doubling if we do nothing else,” a pattern not seen in past outbreaks, House said. Worst-case scenario: The doubling progresses until only those who have recovered from or are less susceptible to the disease remain. But for a disease as deadly as Ebola, “we hope there’s an intervention to stop things before that happens.”

House believes that the unprecedented scale of the current outbreak compared to earlier outbreaks means that it’s less likely to be driven by chance events. “Something fundamental” is different about this outbreak, House said.


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